A team of researchers at the University of Washington has developed robotic, shape-changing smart speakers that can deploy themselves to divide rooms into speech zones and track the positions of individual speakers.
华盛顿大学的一个研究小组开发了一种机器人形状可变的智能扬声器，可以自行部署，将房间划分为语音区，并跟踪单个扬声器的位置。
Using deep learning algorithms, the system is able to allow users to mute certain areas or separate simultaneous conversations, even if two people near each other have similar voices. The robots, each about one inch in diameter, can deploy from, and return to, a charging station on their own, similar to a Roomba.
使用深度学习算法，该系统能够允许用户将某些区域静音或同时进行单独的对话，即使两个相距较近的人的声音相似。这些机器人每个直径约一英寸，可以自行从充电站展开和返回，类似于Roomba。
Unlike previous research on robot swarms, which have required using overhead or on-device cameras, projectors, or special surfaces, the UW team’s system is able to accurately distribute a robot swarm using only sound.
与之前对机器人群的研究不同，之前的研究需要使用头顶或设备上的摄像头、投影仪或特殊表面，UW团队的系统能够仅使用声音准确地分布机器人群。
The team’s prototype is made up of seven small robots that spread themselves across tables of various sizes. As they move from their charger, each robot emits a high-frequency sound. The robots use this frequency and other sensors to avoid obstacles and move without falling off the table.
该团队的原型由七个小型机器人组成，它们分布在各种大小的桌子上。当它们离开充电器时，每个机器人都会发出高频声音。机器人使用这个频率和其他传感器来避开障碍物，移动时不会从桌子上掉下来。
The swarm’s automatic deployment capabilities allow the robots to place themselves with maximum accuracy, permitting greater sound control than if a person set them. The robots disperse themselves as far from each other as possible since greater distances make differentiating and locating people speaking easier.
蜂群的自动部署能力使机器人能够以最大的准确度放置自己，与人工设置相比，可以实现更大的声音控制。机器人尽可能地分散开来，因为更大的距离使区分和定位说话的人变得更容易。
“If I have one microphone a foot away from me, and another microphone two feet away, my voice will arrive at the microphone that’s a foot away first. If someone else is closer to the microphone that’s two feet away, their voice will arrive there first,” co-lead author Tuochao Chen, a UW doctoral student in the Allen School, said. “We developed neural networks that use these time-delayed signals to separate what each person is saying and track their positions in a space. So you can have four people having two conversations and isolate any of the four voices and locate each of the voices in a room.”
“如果我有一个麦克风离我一英尺远，另一个麦克风距离我两英尺远，我的声音会首先到达一英尺远的麦克风。如果其他人离两英尺远的话筒更近，他们的声音会先到达那里，”合著者之一、华盛顿大学艾伦学院博士生陈拓超说。“我们开发了神经网络，利用这些延时信号来分离每个人在说什么，并跟踪他们在一个空间中的位置。因此，你可以让四个人进行两次对话，隔离四个声音中的任何一个，并在一个房间中定位每个声音。”
Testing the swarms
测试蜂群
The UW team tested the robots in offices, living rooms, and kitchens with groups of three to five people speaking. Across all of these environments, the system was able to discern different voices within 1.6 feet (50 centimeters) of each other 90% of the time, without prior information about the number of speakers.
UW团队在办公室、客厅和厨房测试了机器人，三到五个人一组发言。在所有这些环境中，该系统能够在90%的时间内辨别出相距1.6英尺（50厘米）以内的不同声音，而无需事先了解扬声器的数量。
The system was able to process three seconds of audio in 1.82 seconds on average, which is fast enough for live streaming, but still too slow for real-time communications like video calls.
该系统平均能在1.82秒内处理3秒的音频，这对于直播来说足够快，但对于视频通话等实时通信来说仍然太慢。
As this technology continues to progress, the team says that acoustic swarms could be deployed in smart homes to better differentiate people talking with smart speakers. This could allow only people sitting on a couch, in an “active zone” to vocally control a TV, for example.
随着这项技术的不断进步，该团队表示，声学群可以部署在智能家居中，以更好地区分使用智能扬声器的人。例如，这可能只允许坐在沙发上、处于“活动区”的人用声音控制电视。
The team plans to eventually make microphone robots that can move around rooms, instead of just being limited to tables. They’re also investigating whether the speakers can emit sounds that would allow for real-world mute and active zones, so people in different parts of a room can hear different audio.
该团队计划最终制造出可以在房间里移动的麦克风机器人，而不仅仅局限于桌子。他们还在调查扬声器是否能发出允许真实世界静音和活动区的声音，这样房间不同地方的人就能听到不同的音频。
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标签：people,机器人,robots,声群,each,静音,team,com From： https://www.cnblogs.com/bjrobot/p/18279830